Numerical Linear Algebra on High-Performance Computers
This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers. It provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications. Topics include major elements of advanced-architecture computers and their performance, recent algorithmic development, and software for direct solution of dense matrix problems, direct solution of sparse systems of equations, iterative solution of sparse systems of equations, and solution of large sparse eigenvalue problems. This book supercedes the SIAM publication Solving Linear Systems on Vector and Shared Memory Computers, which appeared in 1990. The new book includes a considerable amount of new material in addition to incorporating a substantial revision of existing text.
Product details
November 1998Paperback
9780898714289
360 pages
255 × 175 × 18 mm
0.6kg
This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Table of Contents
- About the authors
- Preface
- Introduction
- 1. High performance computing
- 2. Overview of current high-performance computers
- 3. Implementation details and overhead
- 4. Performance: analysis, modeling, and measurements
- 5. Building blocks in linear algebra
- 6. Direct solution of sparse linear systems
- 7. Krylov subspaces: projection
- 8. Iterative methods for linear systems
- 9. Preconditioning and parallel preconditioning
- 10. Linear Eigenvalue problems Ax=lx
- 11. The generalized Eigenproblem
- Appendix A. Acquiring mathematical software
- Appendix B. Glossary
- Appendix C. Level 1, 2, and 3 BLAS quick reference
- Appendix D. Operation counts for various BLAS and decompositions
- Bibliography
- Index.